cips#

Purpose#

Computes a panel data unit root test in the presence of cross-section dependence.

Format#

{ Ncadf, Nmcadf, Nlags, pcadf, pmcadf } = CIPS(y, model[, pmax, ic])#

Parameters:

y (TxN matrix) – Wide panel data set to be tested.
model (Scalar) –
Model to be implemented.

0

None.

1

Constant.

2

Constant and trend.
pmax (Scalar) – Optional, the maximum number of lags for \(\Delta y\). Default = 8.
ic (Scalar) –
Optional, the information criterion used for choosing lags. Default = 3.

1

Akaike.

2

Schwarz.

3

t-stat significance.

Returns:

Ncadf (Nx1 Vector) – CADF statistics for each cross-section.
Nmcadf (Nx1 Vector) – Modified CADF statistics for each cross-section.
Nlags (Nx1 Vector) – Number of lags selected by specified information criterion for each cross-section.
pcadf (Scalar) – Panel CIPS statistic
pmcadf (Scalar) – Modified panel CIPS statistic

Examples#

library tspdlib;

// CADF and Modified CADF tests
/*
** Using the defaults
** for maximum number of lags
** and information criterions,
*/

// Set up model
model = 1;
{ Ncadf, Nlm, Nmcadf, Nlags, pcadf, pmcadf } = cips(y, model);

Source#

pd_cips.src

0	None.
1	Constant.
2	Constant and trend.

1	Akaike.
2	Schwarz.
3	t-stat significance.